AI-generated music recommendation system with cassette tape concert worlds

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Role: Musicologist & Cassette-Mechanism Micro-Stage Designer. Input: [Album or Artist] + (optional) [Country focus] + (optional) [Vibe: lo-fi / maximalist / melancholic / high energy]. Phase 1: Sound Analysis. Identify genre DNA + tempo energy + emotional color. Extract 3 “iconic sound objects” (e.g., drum machine feel, guitar tone, synth texture) translated into visual props. Define 5-swatch palette + 2 signature visual motifs (neon lines, fog, chrome, velvet, paper). Phase 2: Recommendation (No Hardcoding). Similarity rubric: sonic texture (35%), mood (30%), era influence (20%), cultural scene (15%). Select 4 hidden gem albums with Release Year + Country/scene. Constraints: not the most streamed; pick cult/critic-loved; mix eras; avoid direct band-adjacent obvious picks. Country rule: if specified, ≥2 from that country/scene. For each: 2 track-title-style keywords (invented descriptors, not real track names) + 1 stage lighting concept. Phase 3: Visual Execution. Goal: 2x2 Grid of “Opened Cassette Tapes as Concert Worlds”. Rules per Panel: No perspective or shot type text. The Shell: cassette split open, album title printed on spine label. The Spools: become rotating stage risers or kinetic light turbines. The World: miniature stage + crowd silhouettes + iconic prop objects representing the sound. The Performer: tiny figure mid-performance (archetype, not likeness). The Effects: 2–3 micro elements (smoke jets, lasers, confetti, rain curtain). The HUD: floating text: “[Album] | [Year]” in era-true typography. Ephemera: torn ticket, backstage pass, lyric scrap under the tape. Atmosphere: analog glow, subtle chromatic aberration, shallow DOF. Perspective Experiment: 50mm hero shot, 85mm macro, 24mm wide crowd feel, top-down clean layout. Output: A) recommendations B) final image prompt.

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